ABOUT ARTOS: At Artos, we build tools that help biopharma companies create and manage their R&D documentation in a fraction of the time. If you’re looking to join a team whose mission is to fundamentally change the way that drug development gets done, we’d love to talk to you. About the Role: We're growing fast, and we're looking for an engineer who thrives in a high-velocity environment and wants to do meaningful work. At Artos, you'll help accelerate development of a platform that supports companies — from innovative biotech startups to the world's largest pharmaceutical firms — in delivering life-saving treatments to patients faster than ever before. As a core member of Artos's engineering team, you'll play a critical role in developing, scaling, and expanding the Artos platform to serve regulatory needs for pharma and life science companies around the globe. Qualifications: - BS/MS in Computer Science, Engineering, or related field (or equivalent experience) - 3+ years in software development with a focus on AI/ML applications - Hands-on experience with GenAI applications: prompt engineering, RAG, data pipelines, and eval frameworks - Experience building APIs with modern Python frameworks (FastAPI, Django, etc.) - Experience deploying and scaling containerized apps in cloud environments (AWS preferred) - Experience building CI/CD pipelines for production backend systems - Familiarity with secure coding practices, ideally from a regulated industry (fintech, life sciences) - Pluses: IaC (Terraform/Pulumi), React, knowledge of life sciences regulatory requirements Requirements: - Design, build, and maintain scalable backend systems in production - Build APIs and services using Python frameworks (FastAPI, Django, etc.) - Work with containerized apps and cloud infrastructure (Docker, AWS, Terraform) - Implement CI/CD pipelines and debug production systems - Rapidly apply LLM techniques: prompt engineering, fine-tuning, RAG - Stay current with generative AI best practices and apply them pragmatically - Communicate technical decisions clearly to both technical and non-technical audiences - Collaborate across teams (product, medical writers, customer success) - Navigate ambiguous requirements and execute independently - Debug across system layers: application logic, model behavior, APIs, infrastructure Other Information: Very comfortable working in a fast-paced and intense startup environment Willing to work in-person in our office in Mission Bay 4-5 days/week Likes matcha KitKats, believes every LLM prompt is just Schrodinger’s cat waiting to be observed, and knows too many random facts about the Mongol postal system